Daily Archives: April 14, 2026
Microservices at Scale: Engineering Debt and System Complexity
ELT: Elastic Looped Transformers for Visual Generation
We introduce Elastic Looped Transformers (ELT), a highly parameter-efficient class of visual generative models based on a recurrent transformer architecture. While conventional generative models rely on deep stacks of unique transformer layers, our approach employs iterative, weight-shared transformer blocks to drastically reduce parameter counts while maintaining high synthesis quality. To effectively train these models for image and video generation, we propose the idea of Intra-Loop Self Distillation (ILSD), where student configurations (intermediate loops) are distilled from the teacher configuration (maximum training loops) to ensure consistency across the model’s depth in a single training step. Our framework yields a family of elastic models from a single training run, enabling Any-Time inference capability with dynamic trade-offs between computational cost and generation quality, with the same parameter count. ELT significantly shifts the efficiency frontier for visual synthesis. With reduction in parameter count under iso-inference-compute settings, ELT achieves a competitive FID of on class-conditional ImageNet and FVD of on class-conditional UCF-101. — Read More
The Three Enterprise Layers Are Collapsing Into One
For twenty years, enterprise software that processed decisions at scale had a clean three-layer separation. The CRM layer owned the customer touchpoint — above the glass, the intake, the first interaction. Behind it sat the orchestration layer — workflow engines, business rules, approval chains, human queues. Behind that sat the back-office actions: disbursement, fulfillment, settlement, reconciliation. Below the glass.
A loan application entered through the CRM. A workflow engine routed it through underwriting queues, compliance checks, and approval chains. When the process completed, a back-office system disbursed the funds. Three systems. Three vendor contracts. Three integration projects. An entire consulting ecosystem existed to wire them together, and an entire certification industry existed to staff the wiring. — Read More
What is the Application Layer?
Model companies are moving up the stack. Anthropic has grown on the back of Claude Code and competes directly with Cursor. OpenAI bought OpenClaw. Both are forward deploying engineers into enterprises to embed their models into workflows. On the surface, the application layer looks like it’s being subsumed from below.
On a closer look though, I think it’s premature to call the application layer won by the model companies. The more model companies push into applications, the clearer it becomes where they cannot win. But to see why means understanding what an AI application actually is, because it’s not what most people think. — Read More
On Anthropic’s Mythos Preview and Project Glasswing
The cybersecurity industry is obsessing over Anthropic’s new model, Claude Mythos Preview, and its effects on cybersecurity. Anthropic said that it is not releasing it to the general public because of its cyberattack capabilities, and has launched Project Glasswing to run the model against a whole slew of public domain and proprietary software, with the aim of finding and patching all the vulnerabilities before hackers get their hands on the model and exploit them.
… This is very much a PR play by Anthropic—and it worked. Lots of reporters are breathlessly repeating Anthropic’s talking points, without engaging with them critically. OpenAI, presumably pissed that Anthropic’s new model has gotten so much positive press and wanting to grab some of the spotlight for itself, announced its model is just as scary, and won’t be released to the general public, either. — Read More
What hackers talk about when they talk about AI: Early-stage diffusion of a cybercrime innovation
The rapid expansion of artificial intelligence (AI) is raising concerns about its potential to transform cybercrime. Beyond empowering novice offenders, AI stands to intensify the scale and sophistication of attacks by seasoned cybercriminals. This paper examines the evolving relationship between cybercriminals and AI using a unique dataset from a cyber threat intelligence platform. Analyzing more than 160 cybercrime forum conversations collected over seven months, our research reveals how cybercriminals understand AI and discuss how they can exploit its capabilities. Their exchanges reflect growing curiosity about AI’s criminal applications through legal tools and dedicated criminal tools, but also doubts and anxieties about AI’s effectiveness and its effects on their business models and operational security. The study documents attempts to misuse legitimate AI tools and develop bespoke models tailored for illicit purposes. Combining the diffusion of innovation framework with thematic analysis, the paper provides an in-depth view of emerging AI-enabled cybercrime and offers practical insights for law enforcement and policymakers. — Read More
Anthropic Just Dropped Managed Agents (10x Faster AI Development)
Most AI agents fail in production not because the model is bad, but because keeping them running reliably costs months of engineering work that has nothing to do with the actual agent. Sandboxed containers, credential handling, state management, error recovery, all of it falls on your team before a single user ever sees the thing.
On April 8, 2026, Anthropic launched Claude Managed Agents in public beta, and the core pitch is simple: they handle that infrastructure layer, you handle the agent logic. — Read More
China’s humanoid robot reaches 10 m/s sprint, edges closer to Usain Bolt’s record
Unitree Robotics has released a video showing its H1 humanoid robot reaching a sprint speed of up to 10 meters per second, claiming a new world record.
Tested on an athletics track, the robot recorded 10.1 meters per second as it passed a speed-measurement device, though the company noted a possible measurement error. — Read More
We gave an AI a 3 year retail lease in SF and asked it to make a profit
At Andon Labs, we have been deploying AI agents into the real world, giving them real tools and real money and documenting the consequences. You may know us as the creators of Claudius, the AI running a vending machine at Anthropic’s office. But frontier models have become really good, and running vending machines is too easy for them now. Thus, we decided to make it harder. We signed a 3 year lease for retail space in San Francisco (at 2102 Union St in Cow Hollow) and gave it to an AI to do whatever it wanted with it.
The store is named Andon Market and the AI’s name is Luna. But entering the store, you might ask “what is so AI about it? There are human employees here”. Yes, they are here because Luna knew that she needed them, so she posted job listings, held phone interviews and in the end made a hiring decision. Everything else you see, from the item selection, to the prices, to the opening hours, to the mural on the wall, was decided by Luna. She has a corporate card, a phone number, email, internet access and eyes through security cameras. — Read More
Rick's Cafe AI 